• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.420-422
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• 2023

본 연구는 웨어러블 디바이스를 활용하여 장애인 재활운동 보조를 위한 AI 기반의 맞춤형 서비스 개발을 소개한다. 해당 서비스는 웨어러블 디바이스를 장착한 상태로 운동 중인 사용자의 심박수, 소모 칼로리, 운동 시간 등의 센서 데이터를 수집 및 관리한다. 사용자 생체 데이터는 클라이언트 서버 간 실시간 통신으로 관리되며, django rest framework 로 구축된 서버에 저장된다. 제안 시스템을 통해 수집된 데이터는 시계열 군집화 분석을 위해 k-means clustering 과 k-shape clustering 을 활용하여 체력 평가의 핵심 지표인 심박수를 분석하였다. 특히, 상대적으로 운동이 어려운 장애인 사용자를 위한 맞춤형 운동능력 분석 및 해석에 대한 정보 제공이 가능하다.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.496-513
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• 2022

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 추계학술발표대회
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• pp.931-934
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• 2019

Research using artificial intelligence to generate captions for an image has been studied extensively. However, these systems are unable to create creative stories that include more than one sentence based on image content. A story is a better way that humans use to foster social cooperation and develop social norms. This paper proposes a framework that can generate a relatively short story to describe based on the context of an image. The main contributions of this paper are (1) An unsupervised framework which uses recurrent neural network structure and encoder-decoder model to construct a short story for an image. (2) A huge English novel dataset, including horror and romantic themes that are manually collected and validated. By investigating the short stories, the proposed model proves that it can generate more creative contents compared to existing intelligent systems which can produce only one concise sentence. Therefore, the framework demonstrated in this work will trigger the research of a more robust AI story writer and encourages the application of the proposed model in helping story writer find a new idea.

• 한국산업융합학회 논문집
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• 제27권2_2호
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• pp.445-456
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• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1998년도 공동추계학술대회 경제위기 극복을 위한 정보기술의 효율적 활용
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• pp.913-928
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• 1998

• 한국IT서비스학회지
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• 제20권3호
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• pp.41-56
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• 2021

New drug discovery and development research enable clinical treatment that saves human life and improves the quality of life, but the possibility of success with new drugs is significantly low despite a long time of 14 to 16 years and a large investment of 2 to 3 trillion won in traditional methods. As artificial intelligence is expected to radically change the new drug development paradigm, artificial intelligence new drug discovery and development projects are underway in various forms of collaboration, such as joint research between global pharmaceutical companies and IT companies, and government-private consortiums. This study uses the TOE framework and the Value-based Adoption Model, and the technical, organizational, and environmental factors that should be considered for the acceptance of AI technology at the level of the new drug research organization are the value of artificial intelligence technology. By analyzing the explanatory power of the relationship between perception and intention to use, it is intended to derive practical implications. Therefore, in this work, we present a research model in which technical, organizational, and environmental factors affecting the introduction of artificial intelligence technologies are mediated by strategic value recognition that takes into account all factors of benefit and sacrifice. Empirical analysis shows that usefulness, technicality, and innovativeness have significantly affected the perceived value of AI drug development systems, and that social influence and technology support infrastructure have significant impact on AI Drug Discovery and Development systems.

• 벤처창업연구
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• 제18권5호
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• pp.159-174
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• 2023

본 논문에서는 효과적으로 AI 프로젝트 및 신사업을 선정할 수 있는 방법론을 제안했다. AI 기술은 다양한 산업 분야에서 기업의 비즈니스를 고도화하고 산업 전체의 부가가치를 증대시킬 수 있는 기술이다. 기업가정신 연구 분야에서도 AI 기술은 중요한 소재가 되고 있다. 기업들은 AI 기술을 이용해 새로운 비즈니스를 창업하거나 기존 기업 내에서 신사업을 추진하고 혁신을 추진한다. 그러나 기업에서 AI 프로젝트를 선정하고 추진하는 의사결정 과정에서는 다양한 제약사항과 어려움이 존재한다. 본 논문에서는 모폴로지(Morphology)와 AHP 및 TOPSIS 결합 모형을 통한 AI 프로젝트 선정의 새로운 방법론을 제안한다. 제안 방법론은 AI 기술의 기술적 타당성과 현업의 사용자 요구조건을 동시에 고려하여 AI 프로젝트를 선정할 수 있도록 도와준다. 이 연구에서는 HR 분야의 다수 AI 프로젝트를 결정하고자 하는 실제 기업에 제안 방법론을 적용하고 그 결과를 평가했다. 이를 통해 방법론의 현실 적용 가능성을 확인하였으며, 기업의 AI 프로젝트 관련 의사결정에 유용하게 활용하기 위한 방법을 제시했다. 이 연구에서 제안하는 방법론은 사내 기업가정신(Intrapreneurship) 효과를 증진시키는 차원에서, 기업이 고려하는 여러 AI 프로젝트에 대하여 합리적인 방법으로 선정에 대한 의사결정의 프레임워크를 제시한다는 점에서 의미가 크다.

• 한국IT서비스학회지
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• 제20권1호
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• pp.29-40
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• 2021

North Korea's science and technology policies are being pursued under strong leadership and control by the central government. In particular, a large part of the research and development of science and technology related to the Fourth Industrial Revolution in North Korea is controlled and absorbed by the defense organizations under the national defense-oriented policy framework, among which North Korea is making national efforts to develop advanced technologies in artificial intelligence and actively utilize them in the military affairs. The future weapon system based on AI will have superior performance and destructive power that is different from modern weapons systems, which is likely to change the paradigm of the future battlefield, so a thorough analysis and prediction of the level of AI militarization technology, the direction of development, and AI-based weapons system in North Korea is needed. In addition, research and development of South Korea's corresponding weapon systems and military science and technology are strongly required as soon as possible. Therefore, in this paper, we will analyze the level of AI technology, the direction of AI militarization, and the AI-based weapons system in North Korea, and discuss the AI military technology and corresponding weapon systems that South Korea military must research and develop to counter the North Korea's. The next study will discuss the analysis of AI militarization technologies not only in North Korea but also in neighboring countries in Northeast Asia such as China and Russia, as well as AI weapon systems by battlefield function, detailed core technologies, and research and development measures.

• 한국IT서비스학회지
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• 제21권2호
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• pp.61-84
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• 2022

With the recent application of deep learning to Natural Language Processing (NLP), the performance of NLP has improved significantly and NLP is emerging as a core competency of organizations. However, when encountering NLP use cases that are sporadically reported through various online and offline channels, it is often difficult to come up with a big picture of how to understand and interpret them or how to connect them to business. This study presents a framework for systematically analyzing NLP use cases, considering the characteristics of NLP techniques applicable to almost all industries and business functions, environmental changes in the era of the Fourth Industrial Revolution, and the effectiveness of adopting NLP reflecting all business functional areas. Through solving research questions based on the framework, the usefulness of it is validated. First, by accumulating NLP use cases and pivoting them around the business function dimension, we derive how NLP techniques are used in each business functional area. Next, by synthesizing related surveys and reports to the accumulated use cases, we draw implications for each business function and major NLP techniques. This work promotes the creation of innovative business scenarios and provides multilateral implications for the adoption of NLP by systematically viewing NLP techniques, industries, and business functional areas. The use case analysis framework proposed in this study presents a new perspective for research on new technology use cases. It also helps explore strategies that can dramatically improve organizational performance through a holistic approach that encompasses all business functional areas.

• 인터넷정보학회논문지
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• 제22권6호
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• pp.141-150
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• 2021

인공지능(Artificial Intelligence) 기술을 활용하여 인공지능 기반의 전쟁 (AI-enabled warfare)가 미래전의 핵심이 될 것으로 예상한다. 자연어 처리 기술은 이러한 AI 기술의 핵심 기술로 지휘관 및 참모들이 자연어로 작성된 보고서, 정보 및 첩보를 일일이 열어확인하는 부담을 줄이는데 획기적으로 기여할 수 있다. 본 논문에서는 지휘관 및 참모의 정보 처리 부담을 줄이고 신속한 지휘결심을 지원하기 위해 언어 모델 기반의 다출처 정보 통합 (Language model-based Multi-source Information Integration, LAMII) 프레임워크를 제안한다. 제안된 LAMII 프레임워크는 자기지도 학습법을 활용한 언어 모델에 기반한 표현학습과 오토인코더를 활용한 문서 통합의 핵심 단계로 구성되어 있다. 첫 번째 단계에서는, 자기지도 학습 기법을 활용하여 구조적으로 이질적인 두 문장간의 유사 관계를 식별할 수 있는 표현학습을 수행한다. 두 번째 단계에서는, 앞서 학습된 모델을 활용하여 다출처로부터 비슷한 내용 혹은 토픽을 함양하는 문서들을 발견하고 이들을 통합한다. 이 때, 중복되는 문장을 제거하기 위해 오토인코더를 활용하여 문장의 중복성을 측정한다. 본 논문의 우수성을 입증하기 위해, 우리는 언어모델들과 이의 성능을 평가할 때 활용되는 대표적인 벤치마크 셋들을 함께 활용하여 이질적인 문장간의 유사 관계를 예측의 비교 실험하였다. 실험 결과, 제안된 LAMII 프레임워크가 다른 언어 모델에 비하여 이질적인 문장 구조간의 유사 관계를 효과적으로 예측할 수 있음을 입증하였다.